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Title: Neutral emergence and coarse graining cellular automata
Author: Weeks, Andrew
ISNI:       0000 0004 2720 8741
Awarding Body: University of York
Current Institution: University of York
Date of Award: 2010
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Emergent systems are often thought of as special, and are often linked to desirable properties like robustness, fault tolerance and adaptability. But, though not well understood, emergence is not a magical, unfathomable property. We introduce neutral emergence as a new way to explore emergent phenomena, showing that being good enough, enough of the time may actually yield more robust solutions more quickly. We then use cellular automata as a substrate to investigate emergence, and find they are capable of exhibiting emergent phenomena through coarse graining. Coarse graining shows us that emergence is a relative concept - while some models may be more useful, there is no correct emergent model - and that emergence is lossy, mapping the high level model to a subset of the low level behaviour. We develop a method of quantifying the 'goodness' of a coarse graining (and the quality of the emergent model) and use this to find emergent models - and, later, the emergent models we want - automatically.
Supervisor: Stepney, Susan ; Polack, Fiona Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available